web-scraper: Intelligent web scraping Claude Code skill with automatic strategy selection and TypeScript-first Apify Actor

by yfe404 · Claude Skill · ★ 85

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 72/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

apifyclaude-codeclaude-skillscrawleeplaywrighttypescriptweb-scraping

Quick Facts

Stars85
Forks19
LanguageTypeScript
CategoryClaude Skill
LicenseMIT
Quality Score72/100
Open Issues3
Last Updated2026-03-18
Created2025-10-22
Platformsbrowser, claude-code, node
Est. Tokens~12k

About web-scraper

Web Scraping Skill Intelligent web scraping with automatic strategy selection and TypeScript-first Apify Actor development. Overview This skill provides: Adaptive reconnaissance - Phases 0-5 with quality gates that skip unnecessary work (curl first, browser only if needed) Framework-aware detection - Identifies site framework before searching, skips irrelevant patterns Validated findings - Every...

Compatible Skills

These tools work well together with web-scraper for enhanced workflows:

  • oxylabs-ai-studio-js — semantic(0.33)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • charlotte — semantic(0.31)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)
  • opencode-browser — semantic(0.26)+complementary+rare_topics+same_lang+similar_pop+shared_platform (58%)
  • camofox-mcp — semantic(0.25)+complementary+rare_topics+same_lang+similar_pop+shared_platform (58%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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